By Laurent Colombant, EMEA Payment Integrity Solution Lead at SAS.

For leaders managing capital-intensive projects, the challenge of controlling fraud, error, waste, and abuse (FEWA) is ever-present. A common question which is often raised is, ‘How can we secure our investments, while navigating complex supply chains and high-risk environments?’

Neglecting robust anti-fraud measures carries significant risks, as FEWA can erode up to 5% of company spend with annual losses in the UK from procurement fraud alone of £133.6 billion. Complex supply chains and high-pressure timelines create vulnerabilities, which can be exploited by bad actors.

However, there are strategies that leaders of capital-intensive projects can follow to strengthen their defences. Integrating data analytics, fostering a top-down ethical culture, and leveraging third-party data are essential factors for organisations which are looking to detect and prevent FEWA effectively.

More often than not high capital spend projects are complex, requiring millions if not billions of dollars to be spent in a short period of time with suppliers that aren’t necessarily well known and in countries that are even less known. The risk combination can spell disaster if not well controlled. Historically, companies have conducted these types of checks and balances manually or semi-manually on an ad hoc basis, but this isn’t sufficient anymore and analytics powered by cloud computing make another route possible today.

Integrating data analytics

Cloud-based analytics can play a pivotal role in detecting and preventing FEWA in capital-intensive projects. In such projects, vast amounts of data are generated every day for accounting and resource planning, and if this data is analysed effectively, patterns and anomalies which are indicative of FEWA can be identified swiftly and automatically.

By identifying these patterns and anomalies quickly, organisations can document and validate the findings, and take corrective as well as preventative actions to strengthen their internal controls and avoid financial and reputational losses. This ensures a quick mitigation of risks, which is key for prevention of future occurrences of fraud, abuse and waste – not to mention errors.

Real-time data monitoring systems allow for continuous oversight of transactions and activities. They can flag suspicious activities (in particular in payments) as it occurs, enabling prompt human investigation and response. For example, an unusual spike in procurement costs or repetitive minor billing discrepancies could signal potential fraud or waste. The procurement integrity (PI) solution will automatically identify the signals from millions of data items and guide the investigator in creating a case with substantiated evidence if need be.

Organisations can also identify potential risks before they materialise, by employing predictive analytics. Machine learning algorithms can analyse historical data to identify these risks,and go on to predict where and when fraud or errors are most likely to occur. This proactive approach helps capital-intensive projects to allocate resources to areas of high risk more efficiently.

The PI solution can ensure that even the most subtle discrepancies are identified by producing regular and comprehensive audits, powered by advanced data analytics. These audits can be automated to a significant extent, reducing the manual workload of employees, while simultaneously enhancing their accuracy.

Fostering a top-down ethical culture

Research has found that FEWA is often committed by internal employees and almost a quarter of organisations have experienced collusion both between employees and suppliers, as well as among different suppliers. As such, an organisation’s culture significantly influences its susceptibility to FEWA, and a strong ethical culture, championed by leadership, can deter potential fraudsters and encourage employees to adhere to best practices.

In fact, executives who engage in occupational fraud can cost their business in excess of 10 times more than lower-level employees who are guilty of it. Leaders must be able to exemplify ethical behaviour themselves, and prioritise transparency, because when top executives are visibly committed to combating FEWA, it sets a precedent for the entire organisation. This commitment should be reflected in their policies, communications, and everyday actions.

It is important that regular training programmes which focus on ethical behaviour, FEWA detection, and reporting mechanisms, are implemented across the organisation, so employees can integrate FEWA prevention methods into their own day-to-day work. They should feel empowered to report suspicious activities without fear of retribution, and clear communication channels for reporting and addressing concerns must be established. This is very much in line with and complementary to whistleblowing.

The final step in fostering a top-down ethical approach within an organisation is creating incentives for when this ethical behaviour is demonstrated by employees. This can reinforce a culture of integrity and rewarding employees who have identified and reported FEWA issues not only boosts morale, but also strengthens the internal control environment within the organisation.

Leveraging third-party data

In complex supply chains, where vulnerabilities can arise, relying solely on internal data is insufficient, but third-party data can provide a broader perspective and enhance the accuracy of FEWA detection. Continuous monitoring of suppliers and vendors through third-party data sources can reveal discrepancies which might not be apparent through internal data alone. Not only can external data be used to derive additional insights but also to cleanse and enrich data generated and maintained in ERP systems.

Comparing the ERP data against industry benchmarks can help an organisation to identify outliers, and third-party industry reports and databases can offer valuable insights into standard costs, timelines, and practices. This makes it easier for leaders managing capital-intensive projects to spot any anomalies that might be present within their data.

Organisations can take a further step by partnering with external fraud detection agencies. These agencies often have access to broader data sets and sophisticated analytical tools, which can further strengthen an organisation’s defences against FEWA.

It is evident that leaders managing capital-intensive projects must take a multifaceted approach to manage FEWA effectively. By integrating data analytics, fostering an ethical culture from the top down, and leveraging third-party data, organisations can significantly mitigate the risks associated with complex supply chains and high-risk environments.